University of Cambridge > > Microsoft Research Cambridge, public talks > Automatic Differentiation - Part One: A Revisionist History and the State of the Art

Automatic Differentiation - Part One: A Revisionist History and the State of the Art

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins.

This event may be recorded and made available internally or externally via Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending

Automatic Differentiation (aka Algorithmic Differentiation, aka Computational Differentiation, aka AD) is an established discipline concerning methods of transforming algorithmic processes (ie, computer programs) which calculate numeric functions to also calculate various derivatives of interest, and ways of using such methods. We begin with a discussion of the venerable history of the field, whose roots go back to the dawn of the computer age. There are various “modes” of automatic differentiation, and we will describe forward, reverse, and checkpoint-reverse modes in detail. We then turn our attention to existing systems, with a focus on those able to attain high performance, and the implementation techniques which allow this. These implementations have a variety of weaknesses and restrictions which, we will argue, have impeded the uptake of AD. We close with a benchmark comparing the fastest current systems with our own research prototype compiler based on principles discussed in Part Two. (Joint work with Jeffrey Mark Siskind.)

This talk is part of the Microsoft Research Cambridge, public talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.


© 2006-2023, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity